Improved Prostate-Specific Membrane Antigen (PSMA) Stimulation Using a Super Additive Effect of Dutasteride and Lovastatin In Vitro

Prostate-specific membrane antigen (PSMA)-based imaging improved the detection of primary, recurrent and metastatic prostate cancer. However, in certain patients, a low PSMA surface expression can be a limitation for this promising diagnostic tool. Pharmacological induction of PSMA might be useful to further improve the detection rate of PSMA-based imaging. To achieve this, we tested dutasteride (Duta)-generally used for treatment of benign prostatic enlargement-and lovastatin (Lova)-a compound used to reduce blood lipid concentrations. We aimed to compare the individual effects of Duta and Lova on cell proliferation as well as PSMA expression. In addition, we tested if a combination treatment using lower concentrations of Duta and Lova can further induce PSMA expression. Our results show that a treatment with ≤1 μM Duta and ≥1 μM Lova lead to a significant upregulation of whole and cell surface PSMA expression in LNCaP, C4-2 and VCaP cells. Lower concentrations of Duta and Lova in combination (0.5 μM Duta + 0.5 μM Lova or 0.5 μM Duta + 1 μM Lova) were further capable of enhancing PSMA protein expression compared to a single compound treatment using higher concentrations in all tested cell lines (LNCaP, C4-2 and VCaP)

Global phosphoproteomic profiling reveals perturbed signaling in a mouse model of dilated cardiomyopathy

Phospholamban (PLN) plays a central role in Ca2+ homeostasis in cardiac myocytes through regulation of the sarco(endo)plasmic reticulum Ca2+-ATPase 2A (SERCA2A) Ca2+ pump. An inherited mutation converting arginine residue 9 in PLN to cysteine (R9C) results in dilated cardiomyopathy (DCM) in humans and transgenic mice, but the downstream signaling defects leading to decompensation and heart failure are poorly understood. Here we used precision mass spectrometry to study the global phosphorylation dynamics of 1,887 cardiac phosphoproteins in early affected heart tissue in a transgenic R9C mouse model of DCM compared with wild-type littermates. Dysregulated phosphorylation sites were quantified after affinity capture and identification of 3,908 phosphopeptides from fractionated whole-heart homogenates. Global statistical enrichment analysis of the differential phosphoprotein patterns revealed selective perturbation of signaling pathways regulating cardiovascular activity in early stages of DCM. Strikingly, dysregulated signaling through the Notch-1 receptor, recently linked to cardiomyogenesis and embryonic cardiac stem cell development and differentiation but never directly implicated in DCM before, was a prominently perturbed pathway. We verified alterations in Notch-1 downstream components in early symptomatic R9C transgenic mouse cardiomyocytes compared with wild type by immunoblot analysis and confocal immunofluorescence microscopy. These data reveal unexpected connections between stress-regulated cell signaling networks, specific protein kinases, and downstream effectors essential for proper cardiac function

DIFFERENT DATA JOINING AS A BASIC MODEL FOR HBIM – A CASE PROJECT ST. PATALEIMON IN SKOPJE

H-BIM (Heritage Building Information Modelling) is principle and system of use of historic buildings that can be used for the management, reconstruction or renovation and restoration of monuments. It is a set of geometric and descriptive information about a building. In the last decade, several historical objects were documented using modern methods, mainly advanced photogrammetrical and laser technologies, for a wide range of users to get benefits from economically, safety, presentation, and life cycle management of historical buildings. The rapid development in geomatics is possible thanks to advanced technologies of data capturing, sufficient capacity of computer technology and transmission and information networks. The most used technologies are terrestrial laser scanning (TLS), personal laser scanning (PLS) or mobile mapping systems (MMS), terrestrial or aerial drone based close-range digital photogrammetry (using SfM – structure from motion technology and MVS – multi view stereo). Today’s modern advanced technologies allow geometrical and textural data collection within a few centimetres’ accuracy outside and inside infrastructure by various methods of PLS, photogrammetrical SfM and TLS. In terms of object visualisation, VR or AR (virtual or augmented reality) technology is proving to be suitable. The following text discusses the use of geomatics technologies for the creation of H-BIM on the example of a cultural monument in Skopje, North Macedonia, including visualization in virtual reality (VR)

hArtes: Hardware-Software Codesign for Heterogeneous Multicore Platforms

Developing heterogeneous multicore platforms requires choosing the best hardware configuration for mapping the application, and modifying that application so that different parts execute on the most appropriate hardware component. The hArtes toolchain provides the option of automatic or semi-automatic support for this mapping. During test and validation on several computation-intensive applications, hArtes achieved substantial speedups and drastically reduced development times

Predictions for the future of kallikrein-related peptidases in molecular diagnostics

Kallikrein-related peptidases (KLKs) form a cancer-related ensemble of serine proteases. This multigene family hosts the most widely used cancer biomarker that is PSA-KLK3, with millions of tests performed annually worldwide. The present report provides an overview of the biomarker potential of the extended KLK family (KLK1-KLK15) in various disease settings and envisages approaches that could lead to additional KLK-driven applications in future molecular diagnostics. Particular focus is given on the inclusion of KLKs into multifaceted cancer biomarker panels that provide enhanced diagnostic, prognostic and/or predictive accuracy in several human malignancies. Such panels have been described so far for prostate, ovarian, lung and colorectal cancers. The role of KLKs as biomarkers in non-malignant disease settings, such as Alzheimer’s disease and multiple sclerosis, is also commented upon. Predictions are given on the challenges and future directions regarding clinically oriented KLK research

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases